We focus on the improvement of accuracy of raw text parsing, from the viewpoint of language resource addition. In Japanese, the raw text parsing is divided into three steps: word segmentation, part-of-speech tagging, and dependency parsing. We investigate the contribution of language resource addition in each of three steps to the improvement in accuracy for two domain corpora. The experimental results show that this improvement depends on the target domain. For example, when we handle well-written texts of limited vocabulary, white paper, an effective language resource is a word-POS pair sequence corpus for the parsing accuracy. So we conclude that it is important to check out the characteristics of the target domain and to choose a suitable language resource addition strategy for the parsing accuracy improvement.
@InProceedings{USHIKU16.219,
author = {Atsushi Ushiku and Tetsuro Sasada and Shinsuke Mori}, title = {Language Resource Addition Strategies for Raw Text Parsing}, booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)}, year = {2016}, month = {may}, date = {23-28}, location = {Portorož, Slovenia}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, address = {Paris, France}, isbn = {978-2-9517408-9-1}, language = {english} }
Summary of the paper